Abstract:How to efficiently use hyperspectral remote sensing data to quantitatively retrieve bio-physical and bio-chemical crop parameters and accurately obtain regional crop growth information has always been one of the hot issues in agricultural quantitative remote sensing researches. Based on optimal selection of sensitive hyperspectral bands, the research on retrieval of winter wheat above-ground dry biomass (ADBM) from Hyperion hyperspectral imagery was carried out in Shenzhou County, Hebei Province of Huang-Huai-Hai Plain which was the major grain producing region in China. Firstly, through analyzing relationship and their coefficient of determination (R2) values between field-measured ADBM of winter wheat and narrow band vegetation index (N-VIs) from crop canopy hyperspectral data, the method of determining hyperspectral sensitive band centers based on areas weight of R2 maximum values was proposed and applied. Then, supported by results of hyperspectral sensitive band centers, Hyperion hyperspectral remote sensing data was used to retrieve winter wheat ADBM at regional scale by using the N-VIs, and the accuracy of winter wheat biomass estimation results was validated. The Hyperion remote sensing data was acquired on Apr. 23, 2014, which was at the booting stage of winter wheat, and the used N-VIs included narrow band normalized difference vegetation index (N-NDVI), narrow band difference vegetation index (N-DVI) and narrow band ratio vegetation index (N-RVI). Compared with field-measured winter wheat ADBM, based on optimal selection of sensitive hyperspectral bands and Hyperion N-VIs constructed by the selected sensitive bands, the method of using Hyperion N-VIs to retrieve winter wheat ADBM had better performance, and the accuracy order of winter wheat ADBM of the N-VIs were determined, showing a descending trend as follows: N-NDVI, N-RVI and N-DVI. Among them, based on the Hyperion N-NDVI constructed by the selected sensitive bands (528.57nm and 962.91nm), the retrieval result of ADBM of winter wheat was the best and the relative error (RE) and normalized root mean square error (NRMSE) were 12.65% and 13.78%, respectively. It was proved that based on optimal selection of sensitive hyperspectral bands, using Hyperion N-VIs to retrieve winter wheat ADBM had certain feasibility and effectiveness. It could provide a new thought thread for hyperspectral remote sensing sensitive bands selection and for the improvement of quantitatively retrieving bio-physical and bio-chemical crop parameters.
